Identification and Classification of Conserved RNA Secondary Structures in the Human Genome

By Jakob Skou Pedersen, Gill Bejerano, Adam C. Siepel, Kate R. Rosenbloom, Kerstin Lindblad-Toh, Eric S. Lander, Jim Kent, Webb Miller, David Haussler. PLoS Comput. Biol., 2006

557 citations recorded by the source corpus.

The discoveries of microRNAs and riboswitches, among others, have shown functional RNAs to be biologically more important and genomically more prevalent than previously anticipated. We have developed a general comparative genomics method based on phylogenetic stochastic context-free grammars for identifying functional RNAs encoded in the human genome and used it to survey an eight-way genome-wide alignment of the human, chimpanzee, mouse, rat, dog, chicken, zebra-fish, and puffer-fish genomes for deeply conserved functional RNAs. At a loose threshold for acceptance, this search resulted in a set of 48,479 candidate RNA structures. This screen finds a large number of known functional RNAs, including 195 miRNAs, 62 histone 3′UTR stem loops, and various types of known genetic recoding elements. Among the highest-scoring new predictions are 169 new miRNA candidates, as well as new candidate selenocysteine insertion sites, RNA editing hairpins, RNAs involved in transcript auto regulation, and many folds that form singletons or small functional RNA families of completely unknown function. While the rate of false positives in the overall set is difficult to estimate and is likely to be substantial, the results nevertheless provide evidence for many new human functional RNAs and present specific predictions to facilitate their further characterization.

Subfields: Cancer Research, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/e37092e3694e893fd000c974c899a4acaa1dd522

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Citations in the corpus

Inferring Noncoding RNA Families and Classes by Means of Genome-Scale Structure-Based Clustering (2007, background): “Two of these, EvoFold [10] and RNAz [9,13], are efﬁcient enough to be applied to genome-wide surveys in mammals [10,13] and other metazoan clades [14,15].”
The human mitochondrial transcriptome (2011, unknown): “We also investigated whether other nuclear-encoded ncRNAs, including snoRNAs, scRNAs, and ncRNAs predicted by Evofold (Pedersen et al., 2006) or RNAz (Washietl et al.”
LocARNA-P: accurate boundary prediction and improved detection of structural RNAs. (2012, methodology): “The fast approaches EvoFold and RNAz rely on the given sequence-based whole-genome alignment; they cannot correct potential misalignments, which prevent them from identifying conserved RNA structure.”
MiPred: classification of real and pseudo microRNA precursors using random forest prediction model with combined features (2007, background): “Recently, genome-wide surveys for non-coding RNAs have provided evidence for tens of thousands of previous undescribed evolutionary conserved RNAs with distinctive secondary structures ( 19 ).”
Detection of nonneutral substitution rates on mammalian phylogenies. (2010, background): “However, these methods are all based completely on substitution rates and ignore other sources of information about natural selection, such as patterns of substitution (Moses et al. 2004; Pedersen et al. 2006) or rates and patterns of insertion and”
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Editing modifies the GABAA receptor subunit α3 (2007, methodology): “We have combined bioinformatic analyzes detecting stem–loop structures suitable for A-to-I editing (Pedersen et al. 2006) with an experimental method developed to find novel ADAR substrates that have been edited in a siteselective manner (Ohlson et al.”
UTRdb and UTRsite (RELEASE 2010): a collection of sequences and regulatory motifs of the untranslated regions of eukaryotic mRNAs (2009, methodology): “These include: (i) highly conserved sequence blocks from the 17-way PhastCons vertebrate conserved elements (18); (ii) signiﬁcantly conserved tracts detected by Evofold (19); and (iii) structural conserved non-coding RNAs detected by RNAz (20).”
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